Cost-effectiveness of low-dose colchicine in patients with chronic coronary disease in The Netherlands
Bibliographic record
Abstract
AIMS: Recent trials have shown that low-dose colchicine (0.5 mg once daily) reduces major cardiovascular events in patients with acute and chronic coronary syndromes. We aimed to estimate the cost-effectiveness of low-dose colchicine therapy in patients with chronic coronary disease when added to standard background therapy. METHODS AND RESULTS: This Markov cohort cost-effectiveness model used estimates of therapy effectiveness, transition probabilities, costs, and quality of life obtained from the Low-Dose Colchicine 2 trial, as well as meta-analyses and public sources. In this trial, low-dose colchicine was added to standard of care and compared with placebo. The main outcomes were cardiovascular events, including myocardial infarction, stroke, and coronary revascularization, quality-adjusted life year (QALY), the cost per QALY gained (incremental cost-effectiveness ratio), and net monetary benefit. In the model, low-dose colchicine therapy yielded 0.04 additional QALYs compared with standard of care at an incremental cost of €455 from a societal perspective and €729 from a healthcare perspective, resulting in a cost per QALY gained of €12 176/QALY from a societal perspective and €19 499/QALY from a healthcare perspective. Net monetary benefit was €1414 from a societal perspective and €1140 from a healthcare perspective. Low-dose colchicine has a 96 and 94% chance of being cost-effective, from a societal and a healthcare perspective, respectively, when using a willingness to pay of €50 000/QALY. Net monetary benefit would decrease below zero when annual low-dose colchicine costs would exceed an annual cost of €221 per patient. CONCLUSION: Adding low-dose colchicine to standard of care in patients with chronic coronary disease is cost-effective according to commonly accepted thresholds in Europe and Australia and compares favourably in cost-effectiveness to other drugs used in chronic coronary disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".